Timing for providing relevant notifications for a user based on user interaction with notifications

ABSTRACT

A social networking system provides relevant third-party content objects to users by matching user location, interests, and other social information with the content, location, and timing associated with the content objects. Content objects are provided based on relevance scores specific to a user. Relevance scores may be calculated based on the user&#39;s previous interactions with content object notifications, or based on interests that are common between the user and his or her connections in the social network. Context search is also provided for a user, wherein a list of search of results is ranked according to the relevance score of content object associated with the search results. Notifications may also be priced and distributed to users based on their relevance. In this way, the system can provide notifications that are relevant to user&#39;s interests and current circumstances, increasing the likelihood that they will find content objects of interest.

BACKGROUND

This invention relates generally to social networking, and in particularto the timing for providing relevant notifications for a user of asocial networking system based on the user's interactions with previousnotifications.

Social networking systems have become prevalent in recent years becausethey provide a useful environment in which users can connect to andcommunicate with other users. A variety of different types of socialnetworking systems exist that provide mechanisms allowing users tointeract within their social networks. In this context, a user may be anindividual or any other entity, such as a business or other non-personentity. Accordingly, while enabling social communications among friends,a social networking system can also be a valuable tool for businesses toengage with potential consumers.

However, businesses traditionally have had significant limits onproviding advertisements and information to people that is relevant andtimely for people based on their interests, connections to others, andparticular locations. At best, traditional avenues of providinginformation to users have consistently displayed advertisements atsomewhat arbitrary times, based on basic user-provided profileinformation. Often times, users dismiss the provided advertisementsbecause the advertisements are provided during time periods of the daywhen the users are not available to interact with the advertisementssuch as when at work for example. Third party content providers have yetto examine user engagement with advertisements to identify the mostappropriate time periods throughout the day in which to provide userswith the advertisements.

SUMMARY

To enable a social networking system to provide relevant content objectsto social networking system users, embodiments of the invention providea mechanism for matching user location, interests, and other socialinformation with the content, location, and timing associated withthird-party content objects. In particular, embodiments of the inventionenable relevance scores to be calculated for content objects withrespect to relevance specific to a user of the social networking system,from which a ranked list of content objects can be used for providingnotifications to the user that are relevant to them based on theirinterests, location, and other social information.

In one embodiment, social information is maintained by the socialnetworking system, and a location for a device associated with the useris received. Content objects provided by third parties each are assigneda location, a category, and a delivery time range. The relevance foreach content object with respect to a given user is calculated bymatching up the social information and location of the user with theinformation assigned to the content objects. For example, a severalvalues can be used, including a location value based on proximitybetween the content object and the user device location, an interestvalue based on whether the content of the content object matches theuser's interests, a time value for based on whether the third-partycontent object is ready for delivery, and a connection value based onrelationships that the user's connections have with the content object.The social networking system calculates a relevance score for thecontent objects for the user, and ranks them on this basis. In this way,the social networking system can provide content object-notifications tousers that are relevant to their interests and current circumstances,greatly increasing the likelihood that the user will find the contentobjects of interest.

Accordingly, embodiments of the invention allow the social networkingsystem to evaluate content objects for their relevance to a user beforeproviding them to the user. This functionality allows for user exposureto content objects, e.g., via notifications, that are relevant to theuser's interests, relying on the rich social information provided by thesocial networking service.

In one embodiment, the social networking system provides the contentobject-notifications to users based on user specified preferences. Thepreferences describe when to provide the notifications, the type ofnotifications of interest, and/or the frequency in which to provide thenotifications. In the absence of user specified preferences, the socialnetworking system comprises a default push rate in which to provide thenotifications to users. As the notifications are provided to users, thesocial networking system monitors how users engage with thenotifications. Based on the user engagement, the social networkingsystem may update the frequency in which notifications are provided tothe users, the type of notifications provided to the users, and/or thetime of day when the notifications are provided.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a network diagram of one embodiment of a system for providingsocial networking system user notifications.

FIG. 2 is a diagram of a social networking system, in accordance with anembodiment of the invention.

FIG. 3 is an interaction diagram of one embodiment of a process forproviding relevant notifications for a user of a social networkingsystem based on user location and social information.

FIG. 4 is an interaction diagram for determining when to provide therelevant notifications to the user of the social networking systemaccording to one embodiment.

FIG. 5 is method flow diagram for determining content objects associatedwith a common interest between friends of the social networking systemaccording to one embodiment.

FIG. 6A illustrates a common interest indicated in user profiles offriends in the social network and FIG. 6B illustrates paths of commoninterests between friends in the social network according to oneembodiment.

FIG. 7 is a flow chart showing one embodiment of a process for providingcontext search results to a user of a social networking system, wherethe search results are relevant to the user based on their location andsocial information.

FIG. 8 is a series of sample screenshots illustrating how a clientdevice may display a ranked list of search results to a user of a socialnetworking system, where the search results are presented based on theuser's location and social information.

FIG. 9 is an interaction diagram showing one embodiment of the processfor pricing an advertisement provided to a user of a social networkingsystem, where the advertisement is relevant to the user based on theirlocation and social information.

FIG. 10 is a sample screenshot illustrating an advertisement dashboardallowing a merchant to bid on advertisements provided to users of asocial networking system, where the advertisements are relevant to usersbased on their location and social information.

The figures depict various embodiments of the present invention forpurposes of illustration only. One skilled in the art will readilyrecognize from the following discussion that alternative embodiments ofthe structures and methods illustrated herein may be employed withoutdeparting from the principles of the invention described herein.

DETAILED DESCRIPTION Overview of a Social Networking System Architecture

FIG. 1 is a network diagram of one embodiment of a system 100 forproviding notifications for a user (e.g., member) of a social networkingsystem 130. The system 100 includes one or more user devices 110, one ormore third-party content object provider 120, the social networkingsystem 130 and a network 140. For purposes of illustration, theembodiment of the system 100 shown by FIG. 1 includes a singlethird-party content object provider 120 and a single user device 110.However, in other embodiments, the system 100 may include more userdevices 110 and/or more third-party content object providers 120. Incertain embodiments, the social networking system 130 is operated by thesocial network provider, whereas the third-party content objectproviders 120 are separate from the social networking system 130 in thatthey may be operated by different entities. In various embodiments,however, the social networking system 130 and the third-party contentobject providers 120 operate in conjunction to provide social networkingservices to users of the social networking system 130. In this sense,the social networking system 130 provides a platform, or backbone, whichother systems, such as third-party content object providers 120, may useto provide social networking services and functionalities to usersacross the Internet.

A user device 110 comprises one or more computing devices that canreceive input from a user and can transmit and receive data via thenetwork 140. For example, the user device 110 may be a desktop computer,a laptop computer, a smart phone, a personal digital assistant (PDAs) orany other device including computing functionality and datacommunication capabilities. The user device 110 is configured tocommunicate with the third-party content object provider 120 and thesocial networking system 130 via the network 140, which may comprise anycombination of local area and/or wide area networks, using both wiredand wireless communication systems. In one embodiment, the user device110 displays content from the third-party content object provider 120and/or from the social networking system 130.

The third-party content object provider 120 comprises one or moresources of content objects, which are communicated to the user device110 at appropriate times. In one embodiment, the third-party contentobject provider 120 is a separate entity from the social networkingsystem 130. For example, the third-party content object provider 120 isassociated with a first domain while the social networking system 130 isassociated with a separate social networking domain. In variousembodiments, the third-party content object provider 120 is located on awebsite or alternatively a server, separate or in conjunction from thewebsite or server that hosts the social networking system 130.

The third-party content objects, as the term is used herein, include anycontent object generated by a third-party content object provider 120rather than by a user of the social networking system 130. Third-partycontent objects include informational content objects, such as movieshow times, movie reviews, restaurant reviews, restaurant menus, productinformation and reviews, etc., as well as incentive content objects,such as coupons, discount tickets, gift certificates, etc. according toone embodiment. In addition, some third-party content objects mayinclude a combination of information and incentives. Other examples ofcontent objects include event content objects associated with an event(e.g., a New Year's Eve party) or ad-hoc gathering objects (e.g., animpromptu gathering of 100 people in Union Square, San Francisco).Examples of content objects and the ways in which content objects may bepresented or used are described below.

The social networking system 130 comprises one or more computing devicesstoring a social network, or a social graph, comprising a plurality ofusers and providing users of the social network with the ability tocommunicate and interact with other users of the social network.According to various embodiments, the social networking system 130 maycomprise a website, or alternatively a server that can be accessedthrough a wired or wireless network 140 by user devices 110 orthird-party content object providers 120. In use, users join the socialnetworking system 130 and then add connections (i.e., relationships) toa number of other users of the social networking system 130 to whom theydesire to be connected. As used herein, the term “friend” refers to anyother user of the social networking system 130 to whom a user has formeda connection, association, or relationship via the social networkingsystem 130. Connections may be added explicitly by a user or may beautomatically created by the social networking systems 130 based oncommon characteristics of the users (e.g., users who are alumni of thesame educational institution). For example, a first user specificallyselects a particular other user to be a friend. Connections in thesocial networking system 130 are usually in both directions, but neednot be, so the terms “user” and “friend” depend on the frame ofreference. Connections between users of the social networking system 130are usually bilateral, or “mutual,” but connections may also beunilateral, or “one-way.” For example, if Bob and Joe are both users ofthe social networking system 130 and connected to each other, Bob andJoe are each other's connections. If, on the other hand, Bob wishes toconnect to Joe to view data communicated to the social networking systemby Joe but Joe does not wish to form a mutual connection, a unilateralconnection may be established. The connection between users may be adirect connection; however, some embodiments of a social networkingsystem allow the connection to be indirect via one or more levels ofconnections or degrees or separation. Using a social graph, therefore, asocial networking system may keep track of many different types ofobjects and the interactions and connections among those objects,thereby maintaining an extremely rich store of socially relevantinformation.

In addition to establishing and maintaining connections between usersand allowing interactions between users, the social networking system130 provides users with the ability to take actions on various types ofitems, or objects, supported by the social networking system 130. Theseitems may include groups or networks (where “networks” here refer not tophysical communication networks, but rather social networks of people,entities, and concepts) to which users of the social networking systemmay belong, events or calendar entries in which a user might beinterested, computer-based applications that a user may use via thesocial networking system 130, transactions that allow users to buy orsell items via the service, and interactions with advertisements that auser may perform on or off the social networking system.

These are just a few examples of the items upon which a user may act ona social networking system, and many others are possible. A user mayinteract with anything that is capable of being represented in thesocial networking system 130 or by an external system of the third-partycontent object provider 120, which is separate from the socialnetworking system 130 and coupled to the social networking system 130via a network 140.

The social networking system 130 is also capable of linking a variety ofentities. For example, the social networking system 130 enables users tointeract with each other as well as receive content from third-partycontent object providers 120 or other entities, or to allow users tointeract with these entities through an API or other communicationchannels.

The social networking system 130 also includes user-generated contentobjects, which enhances a user's interactions with the social networkingsystem 130. User-generated content may include anything a user can add,upload, send, or “post,” to the social networking system 130. Forexample, a user communicates posts to the social networking system 130from a user device 110. Posts may include data such as status updates orother textual data, location information, photos, videos, links, musicor other similar data and/or media. Content may also be added to thesocial networking system 130 by a third-party through a “communicationchannel,” such as a newsfeed or stream.

Content objects, generally, represent single pieces of content that arerepresented as objects in the social networking system 130. In this way,users of the social networking system 130 are encouraged to communicatewith each other by posting text and content objects of various typesthrough various communication channels, increasing the interaction ofusers with each other and increasing the frequency with which usersinteract with the social networking system 130.

FIG. 2 is a diagram of one embodiment of a social networking system 130.The embodiment of a social networking system 130 shown by FIG. 2includes a web server 210, an action logger 215, an API request server220, a relevance and ranking engine 225, a content object classifier260, a notification controller 265, an action log 230, a third-partycontent object exposure log 232, an inference module 275, anauthorization server 235, a search module 280, an ad targeting module285, a user interface module 290, a user profile store 240, a connectionstore 245, a third-party content store 250, and a location store 255. Inother embodiments, the social networking system 130 may includeadditional, fewer, or different modules for various applications.Conventional components such as network interfaces, security mechanisms,load balancers, failover servers, management and network operationsconsoles, and the like are not shown so as to not obscure the details ofthe system.

As described above in conjunction with FIG. 1, the social networkingsystem 130 comprises a computing system that allows users to communicateor otherwise interact with each other and access content as describedherein. The social networking system 130 stores user profiles describingthe users of a social network in a user profile store 240. The userprofiles include biographic, demographic, and other types of descriptiveinformation, such as work experience, educational history, hobbies orpreferences, interests, location, and the like. For example, the userprofile store 240 contains data structures with fields suitable fordescribing a user's profile. When a new object of a particular type iscreated, the social networking system 130 initializes a new datastructure, i.e., a “node” of the corresponding type, assigns a uniqueobject identifier to it, and begins to add data to the object as needed.This might occur, for example, when a user becomes a user of the socialnetworking system 130, the social networking system 130 generates a newinstance of a user profile in the user profile store 240, assigns aunique identifier to the user profile, and begins to populate the fieldsof the user profile with information provided by the user.

In addition, the user profile store 240 may include data structuressuitable for describing a user's demographic data, behavioral data, andother social data. Demographic data typically includes data about theuser, such as age, gender, location, etc., e.g., as included in theuser's profile. Behavioral data typically includes information about theuser's activities within the social networking system 130, such asspecific actions (posts, likes, comments, etc.), activity levels, usagestatistics, etc. Other social data comprises information about the userfrom within the social networking system 130 that is not strictlydemographic or behavioral, such as interests or affinities, etc. In oneembodiment, user's interests may be explicitly specified in the user'sprofile or interests that may be inferred from the user's activities inthe social networking system (e.g., uploaded content, postings, readingof messages, etc). Additionally, the user profile store 240 includeslogic for maintaining user interest information for users according toone or more categories. Categories may be general or specific, e.g., ifa user “likes” an article about a brand of shoes the category may be thebrand, or the general category of “shoes” or “clothing.” Multiplecategories may apply to a single user interest. In addition, the userprofile store 240 may be accessed by other aspects of the socialnetworking system 130.

For example, the user profile store 240 includes logic for maintaininginterest information for users according to one or more categories.Categories may be general or specific, e.g., if a user “likes” anarticle about a brand of shoes the category may be the brand, or thegeneral category of “shoes” or “clothing.” Multiple categories may applyto a single user interest. In addition, the user profile store 240 maybe accessed by other aspects of the social networking system 130.

The social networking system 130 further stores data describing one ormore connections between different users in a user connection store 245.The connection information may indicate users who have similar or commonwork experience, group memberships, hobbies, educational history, or arein any way related or share common attributes. Additionally, the socialnetworking system 130 includes user-defined connections betweendifferent users, allowing users to specify their relationships withother users. For example, user-defined connections allow users togenerate relationships with other users that parallel the users'real-life relationships, such as friends, co-workers, partners, and soforth. Users may select from predefined types of connections, or definetheir own connection types as needed. The connection store 245 includesdata structures suitable for describing a user's connections to otherusers, connections to third-party content object providers 120, orconnections to other entities. The connection stores 245 may alsoassociate a connection type with a user's connections, which may be usedin conjunction with the user's privacy setting, to regulate access toinformation about the user. In addition, the connection store 245 may beaccessed by other aspects of the social networking system 130.

The web server 210 links the social networking system to one or moreuser devices 110 and/or one or more third-party content object providers120 via the network 140. The web server 210 serves web pages, as well asother web-related content, such as Java, Flash, XML, and so forth. Theweb server 210 may include a mail server or other messagingfunctionality for receiving and routing messages between the socialnetworking system 130 and one or more user devices 110. The messages canbe instant messages, queued messages (e.g., email), text and SMSmessages, or any other suitable messaging format.

The Application Programming Interface (API) request server 220 allowsone or more third-party content object providers 120 to accessinformation from the social networking system 130 by calling one or moreAPIs. The API request server 220 also may allow third-party contentobject providers 120 to send information to the social networking systemby calling APIs. For example, a third-party content object provider 120sends an API request to the social networking system 130 via the network140 and the API request server 220 receives the API request. The APIrequest server 220 processes the request by calling an API associatedwith the API request to generate an appropriate response, which the APIrequest server 220 communicates to the third-party content objectprovider 120 via the network 140.

The action logger 215 is capable of receiving communications from theweb server 210 about user actions on and/or off the social networkingsystem 130. The action logger 215 populates the action log 230 withinformation about user actions, allowing the social networking system130 to track or monitor various actions taken by its users within thesocial networking system 130 and outside of the social networking system130. Any action that a particular user takes with respect to anotheruser is associated with each user's profile, through informationmaintained in the action log 230 or in a similar database or other datarepository. Examples of actions taken by a user within the socialnetwork 130 that are identified and stored may include, for example,adding a connection to another user, sending a message to another user,reading a message from another user, viewing content associated withanother user, attending an event posted by another user or other actionsinteracting with another user. When a user takes an action within thesocial networking system 130, the action is recorded in the action log230. In one embodiment, the social networking system maintains theaction log 230 as a database of entries. When an action is taken withinthe social networking system 130, an entry for the action is added tothe action log 230.

The relevance and ranking engine 225 includes logic for calculating arelevance score for third-party content objects relative to a user, forranking the third-party content objects by their relevance scores, andfor selecting third-party content objects for sending to users asnotifications. To calculate the relevance score, the relevance andranking engine 225 determines a location value by comparing the contentobject location and a current location for the user device 210,determines an interest value based on whether the third-party contentobject categories are included in the user's interests, determines atime value based on whether the current time is within the delivery timerange for the third-party content object, and determines a connectionvalue based on how many of the user's connections are associated withthe third-party content object. Then, the relevance and ranking engine225 combines the location value, interest value, connection value, andtime value to determine the relevance score for the third-party contentobject with respect to the user. In one embodiment the values are higherfor a better fit (closer proximity, great similarity, etc.) and approacha value of one, and are multiplied together to yield the relevancescore. From the relevance scores for each third-party content object,the relevance and ranking engine 225 ranks the content objects for auser, e.g., from highest relevance score to lowest. The relevance andranking engine 225 then can select third-party content objects to sendto a notification controller 265, or can serve the highest rankedcontent object directly to the user device 110 as a notification(s).

The content object classifier 260 includes logic for assigning each ofthe third-party content objects a location, a category, and a deliverytime range. Categories may reflect various categories of user interests,and may be associated with the interests themselves, e.g., a user“likes” an article about a brand of shoes and the category is the brand,or the article about the shoe brand is assigned a general category of“shoes” or “clothing.” Multiple categories may apply to a single contentobject. General or specific locations may be assigned to content objectsas well, e.g., a city, a particular street name or intersection, or GPScoordinates. A delivery time range is assigned to each content object,e.g., using a useful range based on the hours the associated business isopen.

Additionally, user actions may be associated with exposure tothird-party content objects from one or more third-party content objectproviders 120. Thus, in conjunction with the action log 230, athird-party content exposure log 232 is maintained of user exposures tosuch objects and when the last exposure occurred. The action logger 215receives data describing a user's interaction with an object and storesit to the third-party content exposure log 232. The third-party contentobject log 270 includes logic for storing user exposures to third-partycontent objects and associations between users and objects. The exposureinformation can be used to determine whether to expose the user to thesame or similar content objects, and for adjusting the ranking andselection of content objects on the basis of whether the user previouslyhas been exposed to the same or similar content object. In addition, ifa user becomes associated with a content object via an action, e.g.,uses an incentive, goes to the location, etc., that information also isstored, and can be used for re-ranking and re-selecting the contentobjects.

The notification controller 265 provides notifications of contentobjects to the user device 110. The notifications of content objects areinitially pushed to the user device 110 according to a default rate.Based on user engagement with the notifications, the notificationcontroller 265 may adjust the rate in which notifications are providedto the user device 110. By adjusting the initial settings, thenotification controller 265 provides notifications of content objects tothe user device 110 when the user is more likely to engage with thenotifications. Additionally, the type of content that is provided to theclient device 110 may be updated based on the user engagement.

The authorization server 235 enforces one or more privacy settings ofthe users of the social networking system 130. A privacy setting of auser determines how particular information associated with a user can beshared. The privacy setting comprises the specification of particularinformation associated with a user and the specification of the entityor entities with whom the information can be shared. Examples ofentities with which information can be shared may include other users,applications, external websites or any entity that can potentiallyaccess the information. The information that can be shared by a usercomprises user profile information like profile photo, phone numbersassociated with the user, user's connections, actions taken by the usersuch as adding a connection, changing user profile information and thelike.

The useful social information that is tracked and maintained by a socialnetworking system can be thought of in terms of a “social graph,” whichincludes a plurality of nodes that are interconnected by a plurality ofedges. Each node in the social graph may represent something that canact on and/or be acted upon by another node. Common examples of nodesinclude users, non-person entities, content objects, groups, events,messages, concepts, and any other things that can be represented by anobject in a social networking system. An edge between two nodes in thesocial graph represents a particular kind of connection between the twonodes, which may result from an action that was performed by one of thenodes on the other node.

The social networking system 130 may receive a request to associate theweb content with a node in the social networking system 130. An externalwebsite (e.g., of the third party content object provider 130)incorporates a tag into the markup language document for the web page(s)of the web content to claim ownership of the pages/domain in the contextof the social networking system 130. In some cases, an entire domain orcollection of web pages is associated with a unique identifier thatassociates the web pages with a node. Once established, the socialnetworking system 130 tracks data associated with the node in the actionlog 230.

Data stored in the connection store 245, the user profile store 240 andthe action log 230 allows the social networking system 120 to generate asocial graph that uses nodes to identify various objects and edgesconnecting nodes to identify relationships between different objects. Anedge between two nodes in the social graph represents a particular kindof connection between the two nodes, which may result from an actionthat was performed by one of the nodes on the other node.

The third-party content object store 250 stores content objects receivedfrom third parties. The third-party content objects includeinformational content objects, such as movie show times, restaurantmenus, etc., as well as incentive content objects, such as coupons,discount tickets, gift certificates, etc. In addition, some third-partycontent objects may include a combination of information and incentives.

The location store 255 stores location information received from userdevices associated with users. The location information used by thesocial networking system 130 may be obtained directly from user devices110, e.g., at the time a notification is to be sent or at variouspredetermined time intervals, or the location information may be a laststored location received from the user device 110. In addition, thelocation store 255 may receive updated location information, e.g., inresponse to a change in the location of a user device 110. In oneembodiment, if an updated location is received, the updated location isprovided to the relevance and ranking engine 225 for re-ranking and/orre-selecting the third-party content objects in view of the updatedlocation information.

In general, the selection or ranking of third-party content objects mayoccur at varying intervals based on several variables, such as always atthe beginning of a period during which a notification would be served,or every X minutes during a period during which notifications will beserved, or every X minutes all the time (e.g., so that it's ready when asearch happens), only in response to a change in location or expirationof a delivery time for a content object, etc. Alternatively, the rankingof third-party content objects may occur as a result of user demand. Theuser may explicitly request the ranking by submitting a request forrelevant information happening within the vicinity of the user. Therequest may be received in response to user selection of a “refresh”element included in a user application associated with the presentdisclosure. The request may also be implicit. For example, uponlaunching of the user application, a request may be automaticallyreceived for the ranking.

The social networking system 130 implements context search using acontext search module 280. Context search results are search resultsthat are relevant to the user based on their current location as well astheir social information. In this way, the context search results aretailored to the user's interests, connections, and location at the timeof the search. The context search module 280 incorporates locationinformation, search results and relevance score information obtainedfrom the relevance and ranking engine 225 in order to provide a rankedlist of search results and/or for selection of third-party contentobjects as the basis for serving notifications.

The ad pricing module 285 combines social information, the current time,and location information to provide relevant advertisements, in the formof notifications, to a user. Advertisements of increased relevance to auser are more likely to result in a purchase. Dividing consumersaccording to their interests based on social information allowsmerchants to calculate the value of their potential customers.Advertisements provided through the social networking system 130 may bepriced according to the value of the customer to the merchant, asindicated by their social information.

The UI (or User Interface) module 290 is configured to display a rankedlist of search results on a client device 110 that have been ranked bythe context search module 280. The UI module 290 is additionallyconfigured to generate an advertisement dashboard for merchantsadvertising through the social networking system 130. The advertisementdashboard allows merchants to control the distribution and price theypay for their advertisements. For both functions, the UI module isconfigured to generate a user interface that a client device 110 or athird-party content object provider (or merchant) 120 may interact with.

An inference module 275 determines overlapping interests between usersin the social networking system 130. By determining the overlappinginterests between a user and his or her friends, the inference module275 may identify which interests may be imputed to the user based on theinterests of the user's friends. Thus, through the user's friends, theinference module 275 allows the social networking system 130 to identifyinterests for the user that are not explicitly indicated by the user.

The third-party content object store 250 stores content objects receivedfrom third parties. The third-party content objects includeinformational content objects, such as movie show times, movie reviews,restaurant reviews, restaurant menus, product information and reviews,etc., as well as incentive content objects, such as coupons, discounttickets, gift certificates, etc. In addition, some third-party contentobjects may include a combination of information and incentives.

The location store 255 stores location information received from userdevices associated with users. The location information used by thesocial networking system 130 may be obtained directly from user devices110, e.g., at the time a notification is to be sent or at variouspredetermined time intervals, or the location information may be a laststored location received from the user device 110. In addition, thelocation store 255 may receive updated location information, e.g., inresponse to a change in the location of a user device 110. In oneembodiment, if an updated location is received, the updated location isprovided to the relevance and ranking engine 225 for re-ranking and orre-selection of the third-party content objects in view of the updatedlocation information.

Selecting Relevant Content Objects for a Social Networking System User

FIG. 3 is an interaction diagram showing one embodiment of the processfor providing a user of a social networking system with notificationsrelevant to the user based on their location, their interests, the time,and social information.

Initially, users, via user devices 110 interact 305 with each other viathe social networking system 130 and with the social networking system130 directly, providing it information about the user such as userinterest and connection information. The social networking system 130maintains 310 the user social information (e.g., interest and connectioninformation for each user. For example, the social networking system 130may categorize the interest information into categories.

The social networking system 130 receives 315 information about thelocation of the user device 110. This information may be obtaineddirectly from the user device 110, e.g., at the time a notification isto be sent or at various time intervals, or the social networking system130 may retrieve a last stored location for the user device 110. Inaddition, when a user device 110 changes locations, the updated locationinformation may be provided to the social networking system 130.

The social networking system 130 also receives 320 third-party contentobjects from one or more third parties 120. The third-party contentobjects include informational content objects, such as movie show times,movie reviews, sale information, restaurant menus, etc., as well asincentive content objects, such as coupons, discount tickets, giftcertificates, etc. In addition, some third-party content objects mayinclude a combination of information and incentives.

After third-party content objects are received 320, they are assigned325 categories, locations, and delivery time ranges. For example,categories may be established by the social networking system 130 thatreflect various categories of interests of users of the socialnetworking system 130. The categories may be associated with theinterests themselves, e.g., if a user “likes” an article about a brandof shoes, the category may be the brand. Alternatively, the socialnetworking system 130 may assign the article about the shoe brand ageneral category of “shoes” or “clothing.” The social networking system130 may assign both of these categories to a single content object;thus, multiple categories may apply to a single content object. Forexample, for an incentive offering 20% off a specialty coffee drink at aparticular coffee shop, the promotion may be assigned a category “food,”type “beverage,” and subtype “coffee.” These tags can be matched tocategories associated with user interests. Locations may be assigned tocontent objects as well. For example, a coupon for $2.00 off of a movieticket at a particular movie theater chain may apply to all theaters inthe chain, or just one theatre. A location may be general, e.g., a city,or specific, e.g., a particular street name, or intersection, or GPScoordinate. One or more such locations are assigned to each contentobject. Finally, a delivery time range is assigned to a content object.The range may reflect appropriate hours for the item. For example, ifthe content object is a coupon for a donut store that is open only inthe morning, the range for the notification likely would correspond tothe hours during which the donut store is open, or some other usefulrange related to the open hours, e.g., fifteen minutes before opening tothirty minutes before closing.

Next, the social networking system 130 calculates 330 a relevance scorefor each third-party content object relative to a particular user of thesocial networking system 130. The social networking system 130 uses thelocation, interest, time, and connection information for the user andthe content objects to calculate the score. For example, the socialnetworking system 130 may first calculate scores for each of thesecategories that are combined to get the relevance score.

In one embodiment, for each third-party content object the socialnetworking system 130 determines a location value based on the proximitybetween the content object location and a current location associatedwith the user device. The social networking system 130 also determinesan interest value based on whether the category or categories assignedto the third-party content object are included in the category orcategories associated with the user's interests. The social networkingsystem 130 also determines a time value based on whether the currenttime is within the delivery time range for the third-party contentobject. For example, a discount coupon for lunch at a restaurant may beassociated with lunch hours and is accordingly promoted moreaggressively during the hours commonly associated with lunch. And thesocial networking system 130 determines a connection value based on howmany, if any, of the user's connections are associated with thethird-party content object. For example, a connection associated withthe content object may include information or an incentive for abusiness that one of the user's connections is currently at, e.g., aconnection of the user is at the frozen yogurt store that the incentiveapplies to. Then, the social networking system 130 combines the locationvalue, interest value, connection value, and time value to determine therelevance score for the third-party content object with respect to theuser. In one embodiment the values are higher for a better fit (closerproximity, great similarity, etc.) and approach one, and are multipliedtogether to yield the relevance score.

From the relevance scores of the third-party content objects, the socialnetworking system 130 selects 335 the third-party content objects for auser, e.g., from a ranking of highest relevance score to lowest, or byselection of the highest relevance scored items. Then, the socialnetworking system 130 can then provide 340 the selected objects to anotification controller for serving to the user, or can directly servethe selected third-party content object to the user as the nextnotification, when one is due. The timing of serving notification isdiscussed further in conjunction with FIG. 4.

Once a user is exposed to a third-party content object, the socialnetworking system 130 stores that exposure. In addition, the socialnetworking system 130 monitors whether the user uses the incentive, goesto the location of the information, or otherwise becomes associated withthe content object, and if so, the social networking system 130 storesthat information.

Timing for Providing Relevant Content Object Notifications to a User

The social networking system 130 provides notifications of contentobjects to user device 110. The notifications are provided to the userdevice 110 during time periods in a day. In one embodiment, the socialnetworking system 130 divides a day into a series of time periods. Thetime periods may comprise various time ranges (e.g., hour ranges) thatrepresent different times of the day in which to provide content objectnotifications. For example, the social networking system 130 may dividea day into a plurality of time periods comprising a first time periodrepresenting working hours, a second time period representing lunchhours, a third time period representing home hours, a fourth time periodrepresenting dinner hours, and a fifth time period representing restinghours. The time periods determined by the social networking system 130are similarly applied to all the days of the week. Alternatively,different time periods are determined by the social networking system130 for given days of the week. For example, the time periods assignedfor weekdays may differ from the time periods assigned for weekends.

In one embodiment, each time period in a day is associated with amaximum number of content object notifications (maximum push rate) thatthe social networking system 130 provides to the user device 110 duringthe time period. The social networking system 130 may provide thenotifications of the content objects to the user device 110 based on adefault push rate of the social networking system 130. For example, thedefault push rate may indicate that the social networking system 130 mayprovide a maximum of “X” content object notifications during a firsttime period of the day and may provide a maximum of “Y” content objectnotifications during a second time period of the day and so on.Alternatively, the default push rate may indicate that the socialnetworking system 130 may provide a maximum of “X” content objectnotifications per hour during the first time period of the day and amaximum of “Y” content object notifications per hour during the secondtime period of the day.

Once the maximum number of content object notifications is provided tothe user device 110 for a given time period, the social networkingsystem 130 determines a length of time until the next notification maybe provided to the user device 110. The social networking system 130 maydetermine the delivery time range for the content objects for the userand the last time in which a content object notification was provided tothe user. Based on the delivery time range and the last time in whichthe content object notification was provided, the social networkingsystem 130 determines when the next notification is provided to the userdevice 110 of the user.

In one embodiment, the maximum number of content object notificationsprovided by the social networking system 130 during each time period maybe the same across all time periods or may vary for each time period.For example, a first time period comprising the times of 9 AM to 6 PMmay be associated with a lower default push rate relative to a secondtime period comprising the times of 6 PM to 10 PM. The first time periodis associated with the lower default push rate because it corresponds tobusiness working hours in which users typically prefer not to receiveany content object notifications. In contrast, the second time periodcorresponds to hours in which users are at typically at home andtherefore prefer to receive content object notifications during thistime period.

The default push rate may also be notification type dependent. That is,the frequency in which the social networking system 130 provides contentobjects to the user device 110 is based on the type of notificationassociated with the objects. For example, incentive type content objectnotifications may be associated with a more frequent default push ratecompared to informational type content object notifications or viceversa. Furthermore, the default push rate may also be content typedependent. In other words, the default push rate may be based on thecontent object included in notifications. For example, notificationsabout shopping may be associated with a more frequent default push ratecompared to the default push rate regarding weather content.

In one embodiment, the social networking system 130 providesnotifications of content objects to the user device 110 based on userpreference settings specified by the user associated with device 110.The social networking system 130 provides the content objectnotifications based on the user preference settings rather than thedefault push rate. The user preference settings supersede default pushrates of the social networking system 130 according to one embodiment.

The user preference settings may comprise a user specified push rate forcontent objects. A single user specified push rate may be applicable toall time periods within a given day. Alternatively, the user preferencesettings may comprises a user specified push rate for each time periodin a day. The user preference settings may also comprise user specificpush rates based on notification type and content type as previouslydescribed above.

The social networking system 130 updates the default push rate or userpreference settings based on user interactions with notifications ofcontent objects. The social networking system 130 identifies userinteractions with notifications of content objects provided to the userdevice 110. As the user of device 110 interacts with the notifications,the interaction is tracked by the action loggers 215 assuming that theuser is connected to the social networking system 130. If the userdevice 110 is not currently connected to the social networking system130, the device 100 may provide these interactions to the socialnetworking system 130. The social networking system 130 may receive theinteractions real time or in batches at predefined times throughout theday. The interactions received at the social networking system arestored by the action logger 215 in the third-party content object log270.

In one embodiment, the social networking system 130 analyzes thethird-party content object log 270 to identify how the user engages withthe notifications provided to user device 110. The social networkingsystem 130 identifies patterns of user engagement with notifications ofcontent objects. The patterns describe the characteristics in which theuser interacted with the notifications. Based on the identifiedpatterns, the social networking system 130 updates the rate in whichcontent object notifications are provided to the user whether it beupdating the default push rate or the user's specified preferences. Notethat the following methods to identify user interaction with thenotifications are only some embodiments of machine learningcharacteristics of the social networking system 130. Differenttechniques may be used in other embodiments of the social networkingsystem 130.

The social networking system 130 may identify a time patterncharacteristic from user engagement with notifications. The time patterncharacteristic is indicative of time periods in which the user of device100 interacts with notifications of content objects and time periods inwhich the user dismisses the notifications. For example, the socialnetworking system 130 identifies a time pattern indicating that the useroften interacts with notifications provided between the hours of 12 PMand 1 PM and from the hours of 7 PM and 10 PM. The social networkingsystem 130 may recognize that all notifications provided outside ofthese time periods are dismissed by the user. Accordingly, the socialnetworking system 130 may update or adjust the default push rate or theuser preference settings to reflect the identified pattern. In otherwords, the social networking system 130 may increase the rate in whichcontent object notifications are provided during the identified timeperiod in which the user frequently interacts with notifications. Thesocial networking system 130 may also decrease the rate in which contentobject notifications are provided for all other time periods of the dayin which the user typically dismisses notifications.

Additionally, the social networking system 130 may identify a geographiclocation pattern characteristic from user engagement with notifications.The geographic location pattern characteristic indicates a geographiclocation(s) where the user frequently interacts with content objectnotifications on device 110. The social networking system 130 analyzesthe third-party content object log 270 to determine the locations of theuser when he or she interacted with content objects. The socialnetworking system 130 identifies the locations where the user morefrequently interacted with content object notifications. For example,the social networking system 130 may identify that the user alwaysinteracts with notifications when the user is in San Jose, Calif., butrarely interacts with the notifications when located in Palo Alto,Calif. Accordingly, the social networking system 130 adjusts the defaultpush rate or user preference settings in order to increase the rate inwhich the user receives notifications while the user is at theidentified location. The social networking system 130 may also decreasethe rate in which the user receives notifications while the user islocated at other locations.

The social networking system 130 may also identify a notification typepattern characteristic from user engagement with notifications. Thenotification type pattern characteristic indicates types ofnotifications frequently interacted with by the user of device 110. Forexample, the social networking system 130 may identify that the userfrequently interacts with incentive content object notifications srather that informational content object notifications. The socialnetworking system 130 accordingly updates the default push rate or theuser preferences settings so that notifications of the identified typeare provided to the user device 110 at the maximum push rate or areprovided more frequently than other notification types that areinteracted with less frequently.

Furthermore, the social networking system 130 may identify a contenttype pattern characteristic from user engagement with notifications. Thecontent type pattern characteristic indicates types of content objects(e.g., genres or categories) frequently interacted with by the user. Thesocial networking system 130 may analyze metadata associated withcontent object notifications specified in the third-party content objectlog 270 that describe the content object notifications interacted withby the user. The social networking system 130 analyzes the metadata todetermine the genres or categories of the content objects that arefrequently interacted with as well as those categories of objects thatare frequently dismissed by the user. For example, the social networkingsystem 130 may identify from the metadata that notifications associatedwith “shoes” are interacted with more frequently by the user incomparison with notifications associated with “food.” Accordingly, thesocial networking system 130 updates the default push rate or the userpreferences settings so that notifications of the identified contenttype are provided to the user device 110 at the maximum push rate or areprovided more frequently than other content types that are interactedwith less frequently.

Note that the identified patterns described above and the adjustment ofthe default push rate and user preference settings are machine learningcapabilities of the social networking system 130. By adjusting theinitial settings, the system 130 provides more meaningful information tothe user of device 110. However, the social networking system 130 mayalso receive updates to the user preference settings from the user ofuser device 110. The updated preference settings may override anyadjustments to the settings made by the social networking system 130according to one embodiment.

Once the push rates are established, whether through machine learning orthrough user specification, the social networking system 130 providesthe notifications of content objects to the user device 110 at themaximum push rate. The social networking system 130 may provide thenotifications at the maximum push rate based on the user's interestsand/or current location. The third-party content objects included in thenotifications are ranked and/or selected based on relevance to the useras previously described above to ensure a higher likelihood that theuser will be interested in the notifications.

FIG. 4 is an interaction diagram for determining when to provide therelevant notifications to the user of the social networking systemaccording to one embodiment. Note that in other embodiments, differentsteps may be performed other than those illustrated in FIG. 4.

Initially, the social networking system 130 establishes 401 time periodsfor a day. That is, the social networking system 130 divides a day intoone or more time periods in which a user of user device 110 will receivenotifications of content objects. For example, the social networkingsystem 130 may divide a day into a “morning” time period, an “afternoon”time period, and a “night” time period where each time period isassociated with a range of hours in the day. For each period, the socialnetworking system 130 establishes 403 a maximum push rate in which toprovide the notifications of content objects to user device 110. Asdescribed previously, the maximum push rate describes the maximum numberof content objects that the social networking system 130 may provide touser device 110 during a time period. The maximum push rate may bespecified in the user's preference settings or be a default maximum pushrate of the social networking system 130.

The social networking system 130 identifies 405 third-party contentobjects for the user, e.g., as described above in conjunction with FIG.3. The identified third-party content objects can be in the form of aranked list according to one embodiment. The social networking system130 provides 407 content object notifications from the ranked list ofthird-party content objects to the user device 110 at the establishedmaximum push rate for each time period. For example, the socialnetworking system 130 may provide a maximum of ten notifications ofcontent objects for each time period in the day. The social networkingsystem 130 receives 409 from the user device 110 any user interactionswith the provided notifications during the time periods. The socialnetworking system 130 may receive the interactions real time or inbatches at a specified time of the day.

The social networking system 130 identifies 411 patterns of userinteractions with the notifications during the time periods. Theidentified patterns may be indicative of a time period(s) or geographiclocation(s) in which the user frequently engages with the notifications,a type of notification frequently interacted with by the user, and/or atype of content object frequently interacted with by the user. Based onthe identified patterns, the social networking system 130 adjusts 413the maximum push rates that were previously established. For example,the social networking system 130 may increase the rate in whichnotifications are provided to the user device 110 when the user is at alocation where he or she frequently engages with notifications. Thesocial networking system 130 then provides 414 notifications of contentobjects at the adjusted maximum rates at the appropriate times.

Identifying Relevant Content Objects Through Friends

The social networking system 130 determines overlapping interestsbetween users in the social networking system 130. For a first user ofthe social networking system 130, the social networking system 130identifies a second user that has a connection with the first user inthe system. The social networking system 130 determines a commoninterest between the first user and second user. The social networkingsystem 130 may impute interests to the first user based on the interestsof other users that are connected to the first user in the socialnetworking system 130. By inferring the first user's interests from hisor her friends, the social networking system 130 may determine contentobject notifications of the user's friends that may also interest thefirst user.

In one embodiment, to determine inferred interests for a first userrelative to another user, the social networking system 130 accesses theconnection store 245 to identify other users of the social networkingsystem 130 that have a connection with the first user. The socialnetworking system 130 accesses a second user's profile from the userprofile store 240 who has a connection with the first user. The socialnetworking system 130 compares the first user's profile with the seconduser's profile to determine a common interest between the first user andthe second user. The social networking system 130 may also review aninterest hierarchy indicated in the second user's profile. The interesthierarchy indicates an ordering of interests by the user. In oneembodiment, the interest hierarchy may be explicitly provided by theuser. The user may provide the hierarchy when establishing or updatinghis or her profile.

Alternatively, the hierarchy may be determined based on the user'sactions or behaviors in the social networking system 130. For example,the user may make frequent posts about “coffee” or variants thereof orupload content associated with “coffee.” Accordingly, the socialnetworking system 130 may determine the user has an interest for coffeein this example and update the user's profile with an indication of aninterest in coffee.

The social networking system 130 calculates a relevance score forcontent object associated with the second user's interests since thefirst user and second user share a common interest. The common interestis an indication to the social networking system 130 that the seconduser's interests may also be of importance to the first user.Accordingly, the social networking system 130 determines whether toimpute the second user's interests to the first user.

In one embodiment, a weighting factor is applied to the relevance scoresince the relevance score is calculated with respect to the second userand does not directly represent the first user's interest in contentobjects associated with the second user's interests. In one embodiment,as the degree of separation increases between the first user and thesecond in the social networking system 130 or as the interests betweenthe users increase, the weighting factor may decrease accordinglythereby decreasing the value of the inferred relevance score. The lowerweighting factor is indicative of the decreasing likelihood that thefirst user will share an interest in content objects of the user that isindirectly connected to the first user in the social networking system135.

For example, for a first degree of separation indicating a directconnection between users and a common interest, a weighting factor of90% may be applied to the relevance score. For the first indirectconnection between users (e.g., second order degree of separation) thesocial networking system 130 may apply a predefined weighting factorsuch as 80%. However, as the degree of separation increases past thesecond order degree of separation, the weighting factor may decrease by20%. For example, a third order degree of separation may cause thesocial networking system 130 to apply a weighting factor of 60% to therelevance score of content objects.

The social networking system 130 calculates the relevance score for thefirst user by multiplying the weighting factor to the relevance score ofa content object for the second user to reduce the value of relevancescore for the object. Once the relevance scores for the first user arecalculated for content objects associated with the second user'sinterests, the social networking system 130 may traverse a path ofscored content objects associated with the interests of the second user.The social networking system 130 may stop traversing the path responsiveto a relevance score for a content object in the path being below athreshold. The social networking system 130 may impute the interests ofthe second user to the first user for those interests that have arelevance score above the threshold.

Alternatively, the social networking system 130 may only impute theinterests of the second user that are related to the common interestbetween the first user and the second user and have an inferredrelevance score above the threshold. Thus, rather than transferring anyof the second user's interests to the first user that have an inferredrelevance score above the threshold, the social networking system 130transfers only the second user's interests that are related to thecommon interest between the first user and second user. For example, thefirst user and second user may have a common interest of “coffee.” Thesecond user may have an interest for specific brands of coffee such as“Starbucks” and “Peets” coffee. Responsive to the relevance score forcontent objects associated with the “Starbucks” and “Peets” coffeeinterest being above the threshold, the social networking system 130 maytransfer these interests to the first user.

In another embodiment, the social networking system 130 may impute theinterests of the second user that are similar to the common interestbased on content. For example, the common coffee interest between thefirst user and second user may be categorized as a “beverage” in thesocial networking system 130. The social networking system 130 maydetermine other interests of the second user that are also categorizedas a “beverage” such as an affinity for “tea” or other interests of thesecond user that have a categorization related to the “beverage”category such as a “food category.” Responsive to the relevance scorefor the interest in tea being above the threshold, the social networkingsystem 130 may transfer the interest to the first user.

In one embodiment, the social networking system 130 may also applydifferent weighting factors based on the type of connection between thefirst user and the second user other than degree of separation. Forexample, “friendship” type connections may be associated with a higherweighting factor than a “work colleague” type connection. The socialnetworking system 130 may apply default weighting factors based on thetype of connections between users. Alternatively, a user may specifyuser preference settings indicating the weight to apply to specifictypes of connections. For example, the user may associate a higherweighting factor with “work colleague” type connections compared to“friendship” type connections.

Once the social networking system 130 calculates the relevance scoresfor interests of the second user, the social networking system 130 mayre-rank the list of previously established content objects, or reselecta set of the objects, related to the first user based on the inferredrelevance scores. Thus, the re-ranked list includes content objectsassociated with the second user's interests that have been transferredto the first user. Alternatively, the social networking system 130 mayinclude the relevance scores during the initial calculation of therelevance scores for content objects of interest to the first user.Thus, the second user's interests are considered when determining whichcontent objects to initially provide to the first user.

FIG. 5 is a flow diagram determining content objects associated with acommon interest between friends of the social networking systemaccording to one embodiment. Note that in other embodiments, differentsteps may be performed other than those illustrated in FIG. 5.

The social networking system 130 identifies, for a first user, a seconduser having a connection with the first user in the social network. Todetermine the connection, the social networking system 130 accesses thefirst user's profile 601 illustrated in FIG. 6A. In the example shown inFIG. 6A, the first user's profile 601 indicates that the first user“Erick” is friends with “John.” Accordingly, the social networkingsystem 130 locates John's user profile 603. Similarly, the second user'sprofile 603 indicates that John is also friends with Erick indicating abidirectional relationship between the users.

The social networking system 130 then identifies 503 an interest commonto the first user and the second user. In the example shown in FIG. 6A,the social networking system 130 compares profiles 601 and 603 toidentify a common interest between the profiles. The comparisonindicates that Erick and John both have an interest for coffee. However,John's profile 603 further indicates that John has an interest forStarbucks coffee followed by Peets coffee and CPK coffee. The socialnetworking system 130 determines that Starbucks is associated with“coffee” due to a Starbucks object 605 indicating that Starbucks is asub-type of “coffee” and has a categorization of “beverage.” A similardetermination is made for Peets coffee and CPK coffee.

The social networking system 130 then calculates 505 a relevance scorefor content objects associated with the common interest. The socialnetworking system 130 first calculates the relevance score for contentobjects associated with the common interest for the second user based onlocation, time, interest, and connection information as previouslydescribed above. To determine the relevance score for the first userthat indicates the measure of likelihood that the first user would alsohave an interest in content objects associated with the interests of thesecond user, the social networking system 130 applies a weighting factorto the relevance scores for the second user. As described previously,the relevance scores for the first user may be used by the socialnetworking system 130 to re-rank or re-select the first user's rankedlist of content object notifications in order to include the seconduser's interests. Alternatively, the social networking system 130 may beused to include content objects associated with the second user'sinterests in the initial determination of the first user's ranked listof content objects.

Referring now to FIG. 6B, a plurality of preference graphs (i.e.,interest trees) are shown for users of the social networking system 130in order to illustrate the calculation of the relevance scores for thefirst user. Each preference graph represents preferences as nodes on thegraph. As shown in FIG. 6B, the preference graph for Erik includes nodesfor Erik's interest for “steak” and “coffee.” In contrast, John'spreference graph includes nodes for John's interests in the movie“Braveheart” as well as the beverages “coffee” and “tea.”

The social networking system 130 may determine John's interests that areassociated with the common coffee interest between Erik and John. Thecoffee node has sub-nodes indicating the brands of coffee preferred byJohn. Each sub-node is associated with content objects corresponding tothe coffee brand represented by the sub-node. The social networkingsystem 130 calculates a relevance score for the content objectsassociated with each sub-node of the coffee node. Thus, the socialnetworking system 130 calculates the relevance score for content objectsassociated with Starbucks, Peets, and CPK coffee. To determine aninferred relevance score for the content objects indicating a measure oflikelihood that Erick would also have an interest in the content objectsassociated with John's interests, the social networking system 130applies a weighting factor to the relevance scores calculated for thecontent objects relevant to John.

Because Erick and John are directly connected in the social networkingsystem 130 indicated by connection 607, a higher weighting value isapplied to John's interests in comparison to the weighting value usedfor users that are not directly connected to Erick in the socialnetworking system 130. In the example shown in FIG. 6B, the socialnetworking system 130's may apply a 90% weighting factor to therelevance scores for content objects associated with John's interests.

The application of the weighting factor to John's relevance scoresresults in a 90% likelihood (i.e., the inferred relevance score) thatErick would have interest in content object notifications associatedwith John's interest for Starbucks. In contrast, there is a 50%likelihood that Erick would be interested in content objectnotifications associated with John's interest for Peets coffee and a 20%likelihood that Erick would be interested in content objectnotifications associated with John's interest for CPK coffee.

In one embodiment, the social networking system 130 may traverse John'spreference tree until a relevance score below a threshold value isreached in order to optimize the search for content objects associatedwith John's interests. The social networking system 130 may traverse thepreference tree in descending order of inferred relevance scores. Oncean interest with an inferred relevance score below a threshold islocated, the traversal of the preference tree is stopped.

In the example in FIG. 6B, assume a threshold of 60% inferred relevancescore. The social networking system 130 may first traverse the pathconnecting the “coffee” node to the “Starbucks” node and determine the90% likelihood that Erick would have interest in content objectnotifications associated with John's interest for Starbucks. However,the traversal of the other paths connected to the “coffee” node isstopped since the path connecting the “coffee” node and “Peets”indicates a 50% likelihood that Erik would have interest in contentobject notifications associated with John's interest for Peets Coffee.The social networking system 130 may then traverse the next path in thepreference graph indicating the John's interest for “tea.” Because thepath indicates a 70% likelihood that Erick would have interest incontent object notifications associated with John's interest for “tea,”the content objects for “tea” are provided to Erik. In contrast, thepath indicating John's interest for the movie “Braveheart” indicates a50% likelihood that Erick would have interest in content objectsassociated with John's interest for the movie. Thus, the socialnetworking system would not continue to traverse any nodes connected tothe “Braveheart” node. Note that FIG. 6B does not illustrate other pathsfrom the “Braveheart” or “tea” nodes for brevity purposes.

As described previously, the social networking system 130 may alsodetermine interests related to the common “coffee” interest based oncontent. In the example illustrated in FIG. 6B, the social networkingsystem may identify that “coffee” is a type of beverage. Accordingly,the social networking system 130 identifies John's interest for othertypes of beverages. In the example, the social networking system 130 maydetermine John's interest for tea which is a type of beverage. Theweighting factor is applied to John's interest for tea indicating a 70%likelihood that Erik may have an interest in John's interest for tea.Because the inferred relevance score for the “tea” interest is greaterthan the threshold, content objects associated with the John's interestfor “tea” may be provided to Erik.

In one embodiment, the social networking system 130 may also calculateinferred relevance scores for users that are indirectly connected to thefirst user. In the example shown in FIG. 6B, Sarah is indirectlyconnected to Erick through John. Specifically, Sarah has a directconnection with John as illustrated by arrow 609. Thus, Sarah has a2^(nd) order degree of separation from Erick. As previously discussed,as the degree of separation increases, the weighting factor applied torelevance scores also decreases.

In the example shown in FIG. 6B, an 80% weighting factor is applied tocontent objects associated with Sarah's interests rather than the 90%weighting factor used to calculate the inferred relevance scores forJohn's interests. The lower weighting factor is applied since Sarah isindirectly connected to Erick in the social networking system. Asdescribed previously, as the degree of separation increases betweenusers, the applied weighting factor decreases.

The application of the weighting factor to Sarah's relevance scores inone or more of the methods described above with respect to John resultsin a 70% likelihood that Erick would have an interest in content objectnotifications associated with Sarah's interest for Seattle's Best and a20% likelihood that Erick would have an interest in content objectnotifications associated with Sarah's interest for “McDonalds” coffee.

The social networking system 130 then provides 507 the content objectnotifications to the first user. The social networking system 130provides content object notifications having an inferred relevance scoreabove a threshold value. The content objects may be provided responsiveto an explicit search query from the first user or may be pushed to thefirst user as previously described above.

Context Search Including Location and Social Relevance Information

FIG. 7 is a flow chart showing one embodiment of a process for providingcontext search results to a user of a social networking system 130. Inone embodiment, context search begins by receiving 705 a search queryfrom a client device 110 associated with a user. Often this will be atext-based query. For example, the search may be for “Italianrestaurants” if the user is looking for an Italian restaurant to eat at.Near the time that the search query is entered by the user, the clientdevice 110 or the social networking system 120 communicating with theclient device determines the current location of the client device 110associated with user. This user location and the search query 705 arecommunicated to the social networking system 130.

Once the context search query and user location has been received 705from the user, the social networking system performs a search to obtain710 search results related to the search query. In one embodiment,performing the search involves searching an external database using asearch engine to obtain the search results 710. For example, the socialnetworking system may search by using an online search engine. Inanother embodiment, performing the search involves searching socialnetworking information to obtain 710 third-party content objects assearch results. Each search result returned by the search may haveassociated with it a search value. The search value is a measure of thequality of the match between the search query and the search result. Ahigher search value indicates that the search engine used to perform thesearch believes that the search result is very close to what the userwas searching for. In one embodiment, the search value varies or isnormalized to vary within a range of 0 to 1, wherein a search value of 1indicating a perfect match. In one embodiment, the received search queryis modified to include the user location before the search is performed,so that the search results are more relevant to the user's currentlocation.

A relevance score is then determined 715 for some or all of the searchresults. The relevance score is determined as described above, howeveradditional factors are taken into account when determining the relevancescore for search results. As described above, the relevance score may bedetermined for third-party content objects (e.g., based on a userinterest in product created by a merchant). In embodiments where thesearch results are obtained from an external search engine, in order forthe system 130 to assign relevance scores to the search results, thesystem first associates, if possible, the search results with one ormore existing third-party content objects already known to the socialnetworking system 130. In one embodiment, the search results areassociated with third-party content objects by matching the searchresult to a category of the third-party content object.

The system 130 then determines the relevance scores for the third-partycontent objects and their associated search results. The relevance scorecalculated for a search result will be based, in part, on its associatedsearch value, in addition to other values such as the location value,time value, connection value, interest value, for example. In someembodiments, part of the search result, e.g., the name of a restaurant,may be used as a filter for which content objects will be used as partof the relevance score.

The relevance score may be determined for all search results, or onlyfor a subset of the search results. In one embodiment, the determinationfor which search results to calculate relevance scores for may be basedon a cutoff threshold, for example relevance scores may only becalculated for those search results with search values greater than 0.5.In another embodiment, the relevance score is only calculated for afixed number of search results, for example the first ten search resultswith the highest search values.

The social networking system 130 may also append additional socialinformation to each search result. The appended information may includethe number and/or identities of the user's friends who have indicated aninterest in the search result, the number and/or identities of friendswho have entered comments regarding the search result, or the identitiesof friends who are currently checked into the location of the searchresult, or who have checked into the location of the search result inthe past.

The search results with associated relevance scores are ranked 720 basedon the relevance scores such that search results with higher relevancescores appear higher in a ranked list of search results. The ranked listof search results may then be provided to the user through the clientdevice 110.

In some embodiments, the relevance scores are calculated prior toperforming the search or obtaining the search results. Then, once thesearch results are obtained, the relevance scores may be adjustedseparately by the search value of the search results. In one embodiment,the adjustment comprises multiplying the search value into the relevancescore to obtain an updated relevance score. In embodiments where therelevance score is calculated prior to obtaining the search results, therelevance scores may be used to improve the search query and thereforeimprove the relevance of the search results to the user. For example, ifthe user's searches for “21^(st) Amendment,” intending to refer to a baror restaurant with that name, many of the search results would otherwiseappear to be unrelated to bars or restaurants. However, in this exampleembodiment, the third-party content store 250 may include a third-partycontent object associated with a restaurant called “21^(st) Amendment”with a high relevance score for a user interest in “restaurants.” As aresult of the high relevance score for restaurants with this searchterm, the search query may be modified to include the term “restaurants”along with “21^(st) Amendment.”

In some embodiments, a search query is not a necessary precondition toperform a context search. A search may be performed by the socialnetworking system 130 by receiving input from a user requesting that allrelevant third-party content objects be ranked or selected for inclusionaccording to their relevance score and immediately forwarded to theuser. This allows a user to effectively “pull” notifications from thesocial networking system without having to wait to be forwarded them.Notifications forwarded to the client device 110 in this manner may beexempted from being counted towards the maximum push rate for the timeperiod in which the user performs the search. Thus, context searchtemporarily overrides the social networking system's 130 control overthe pushing of notifications to the client device 110. In oneembodiment, the search replaces the next notification that would havebeen pushed to the client device 110. In another embodiment, the searchdoes not affect the next notification, and the next notification ispushed to the client device 110 independent of the search. In yetanother embodiment, the search causes the delay of the push of the nextnotification to the client device 110. Context search may also be usedby the social networking system to identify patterns of userinteractions during the time period in which the search occurred. Thus,context search may affect the maximum push rate of notifications duringone or more time periods.

This is useful, for example, if the user is generally interested insocially relevant events going on around them, without having aparticular idea in mind as to what to search for. In an embodiment wherethe user is interested in events in close proximity to their currentlocation, the search will weigh heavily in favor third-party contentobjects with location data that is in close to the user's currentlocation at the time of the search. A list of ranked results or selecteditems is created, where the results are ranked/selected according totheir respective relevance scores as described above. In one example, auser performing a blank context search in accordance with the above maybe provided with context search results indicating that three of theirfriends are at a nearby coffee shop. In this example, the user may notbe particularly interested in coffee, but their proximity to both theirfriends and the coffee shop may affect their decision about what to donext.

FIG. 8 is a series of sample screenshots illustrating how a clientdevice 110 may display a ranked list of search results to a user of asocial networking system 130, where the search results are presentedbased on the user's location and social information. As shown at the topof FIG. 8, a text field 805 is configured to receive a search queryinput. The query button 810 executes a search on the entered searchquery. A ranked list of search results may be displayed in one or moreformats.

In one embodiment, the ranked list of search results is displayed in agraphical format. In the graphical format, the search results aredisplayed as pins 820 (or markers), with the center of each pin 820providing a letter or numerical indication of the relative rank of thesearch result (e.g., “A”, “B”, “C”, or “1”, “2”, “3). The pins areoverlaid on a graphical map 815 that is associated with at least onevalue used to make up the relevance score. In one embodiment, thegraphical map 815 may be a map of a place, for example a portion of acity. In this embodiment, the relevant value for the map is the locationvalue, as the map is based on physical location. Each search result pinis then placed on the map according to the location informationavailable in the third-party content object associated with the searchresult to which pin refers. Inside each pin 815 is an indication of theorder of the search result in the ranked list of search results. Forexample, the search result with the second highest relevance score maybe indicated with a “B” or a “2” depending upon the embodiment. In oneembodiment, the graphical map 815 is centered on the user's location, asdetermined either at the time of the search or as determined later intime.

The ranked list of search results is displayed in a textual format 825in addition to the graphical map 815, or instead of it. In the textualformat, the ranked list of search results appear in text form, rankedaccording to their relevance scores. In one embodiment, the displayedranked list of search results may be appended to include the user'ssocial graph information, for example, likes 830 regarding a givensearch result, or comments 835 from friends regarding that searchresult. Additionally, in the case where the search results are relatedto locations of places or things to do, the displayed ranked list ofsearch results may be appended to include friends or other socialnetwork connections 840 that are currently checked in at the location ofthat search result. For example, a search query for “restaurant” mayindicate that a user has two friends who are currently eating at anearby In-N-Out Burger.

In some embodiments, the displayed textual list of ranked search resultsprovides the user the option of filtering the list of displayed rankedsearch results (not shown). Depending upon the embodiment, the searchresults may be filtered based on location value, time value, connectionvalue, interest value, number of likes, number of comments, or number offriends present or near the location associated with the search result.

FIG. 8 a is a sample screenshot of how a context search query 805 a forcoffee may be displayed according to one embodiment of the presentinvention. Coffee locations may be displayed as pins 820 a, and listed825 a in order according to their relevance scores.

FIG. 8 b is a sample screenshot of how a context search query 805 b forthe locations of friends nearby to a particular location may bedisplayed according to one embodiment of the present invention. In thisexample embodiment, the pins 820 b and text 825 b are displayed andordered according to the relevance scores associated with the locationsat which their friends are present.

FIG. 8 c is a sample screenshot of how a context search query 805 c forthe locations of nearby movies and movie theaters may be displayedaccording to one embodiment of the present invention. In this exampleembodiment, the pins 820 c and text 825 c are displayed and orderedaccording to the relevance scores associated with movie theaters nearbyto the user's location, and the movies those movie theaters arecurrently showing. Critical reviews or star ratings of movies may alsobe displayed.

FIG. 8 d is a sample screenshot of how a context search query 805 d fora restaurant may be displayed according to one embodiment of the presentinvention. For example, if a user is interested in the availability ofreservations for a particular restaurant, this screenshot illustrateshow the social networking system 130 may provide a mechanism for theuser to obtain reservations for a restaurant. The calendar of FIG. 8 dcomprises a number of entries 860, which contain times or slots whichmay be reserved. In one embodiment, the third-party content object forthe relevant restaurant comprises available reservation slots on per daybasis. A user may select a particular reservation time 855 to reserve atable on a future date at a particular time. The screenshot alsoillustrates, for days that have already passed, historical informationregarding which of the user's friends visited 850 that restaurant andwhen. The user may switch between several different timelines selections845, including day, week, and month views of the availability andhistorical information of the restaurant.

The embodiments illustrated in FIGS. 8 c and 8 d are not exclusive tomovie theaters and restaurants specifically. The layout, reservationsystem, and historical information displayed in FIG. 8 d may also beimplemented to assist a user in purchasing movie tickets in advance.Vice versa, the layout of FIG. 8 c (and similarly 8 b and 8 a) may beused to display the location and table availability of a restaurantindicated by a user in the search query field 805.

Pricing Advertisements Based on Location and Social RelevanceInformation

Any notification provided by social networking system 130 may beconsidered an advertisement. This includes traditional advertisementsspecifically created by merchants to be distributed as notifications tousers through the social networking system, as well as notificationsdynamically generated based on the user's social information and searchqueries. For example, a notification indicating that two of a user'sfriends are at a nearby coffee shop is inherently an advertisement forthat coffee shop, even if the purpose of the notification was primarilyto inform the user of the location of their friends. Thus, for purposesof discussion in this section, the terms “advertisement” and“notification” are interchangeable. Advertisements comprise third-partycontent objects including categories, locations, and delivery timinginformation for determining when the advertisements will be provided tothe user. The social networking system 130 may also receive pre-writtenadvertisements from third-party websites. In some cases, theadvertisement may additionally comprise deals or coupons for theaffiliated merchant's goods or services.

The price of advertisements is determined based on the relevance of theadvertisement to the user. In one embodiment, the higher the relevancescore of the advertisement for the user, the more the advertiser pays tothe social networking system 130 to display the advertisement to theuser. In this case, the cost of the advertisement rises in roughapproximation of the expected value of the user to the advertiser. Asabove, the relevance score may be determined based on a location value,an interest value, a connection value, and a time value. For example, ifthe location associated with the advertisement is very close to theuser's location at the time the advertisement is to be sent, this willcause the advertisement to be relatively more expensive than if thelocation is further away from the user's current location. In oneembodiment, as a result of the social networking system having a maximumpush rate for advertisements, advertisements of low relevance and costwill generally be provided less frequently than advertisements of higherrelevance and cost.

FIG. 9 is an interaction diagram showing one embodiment of the processfor pricing an advertisement provided to a user of a social networkingsystem 130, where the advertisement is relevant to the user based on theuser's location and social information. In some cases, the socialnetworking system 130 first receives 905 pre-written advertisements fromthird-party websites. The advertisements comprise third-party contentobjects including categories, locations, and delivery timing informationfor determining when the advertisements will be provided to the user.

At any point in time the social networking system 130 may receive 910 auser location from a client device 110. Based on the current time, theuser's social information, and the received user location, the socialnetworking system 130 determines 915 a notification (or advertisement)to provide to the user. In order to determine which notification toprovide, the system 130 uses the current time, the user's location, andthe user's social information to calculate the relevance of thethird-party content objects stored in the system 130.

The social networking system 130 is notified of which notification is tobe provided to the user. In one embodiment, the system 130 thendetermines 920 the price to be charged to the merchant affiliated withthe notification for providing the notification to the user. Incontrast, in other embodiments, the system 130 may wait until after anindication has been received informing the social networking system 130that the notification has been received, interacted with, or has alteredthe user's behavior to determine a price to be charged to the merchantaffiliated with the notification. In these embodiments, the price mayalso be based on the user's behavior, for example receiving anindication that caused a user merely to enter a store after receiving anotification may result in a notification costing a first price, whereasreceiving an indication that a user made a purchase after receiving anotification may result in a notification costing a second, higherprice.

The social networking system 130 provides 925 the notification to theuser according to the mechanisms provided above. In some cases, thenotification may additionally comprise deals or coupons for theaffiliated merchant's goods or services. The social networking system130 then receives 930 notification feedback regarding the behavior ofthe user in response to the notification. The notification feedback maycomprise one or more of an updated user location, an indication that theuser made a purchase from the affiliated merchant including whether theuser made use of a provided coupon, a purchase amount, or an indicationthat the user paid for a purchase with a credit card or other paymentsystem affiliated with the social networking system 130.

The notification feedback may be used for a number of different purposesdepending upon the embodiment. If the merchant is paying fornotifications based on the results generated by the notification, thesocial networking system 130 uses the notification feedback to price thenotification. The notification feedback may also be used to adjust 935the price of future notifications, for example if the ad wasineffective, the price of the ad may be reduced in the future. In oneembodiment, the notification feedback may be used to adjust therelevance score, and therefore the price, for the third-party contentobject associated with the notification. For example, an indication thata purchase was made based on a notification may be used to increase theinterest value of the third party content object associated with thenotification, which may thereby increase or decrease the price for thatadvertisement depending upon pricing structure implemented by the socialnetworking system 130. Similarly, if the notification was determined tobe relevant based on a high connection value, the connection value maybe increased as a result of the purchase.

In some embodiments, social networking system 130 also takes intoaccount whether the advertisement is being pushed to the client device110, or whether the user has performed a context search pullinginformation about nearby search results to the client device. In oneembodiment, the price of an advertisement is increased if a contextsearch results in an advertisement related to one of the search resultsbeing provided to the user. For example, the price of an advertisementfor STARBUCKS may be more expensive if the user has search for coffeeshops in their immediate vicinity than if the user did not perform asearch and the notification controller 265 is providing the sameadvertisement. In another embodiment, the higher the relevance score ofthe advertisement for the user, the less costly the advertisement is tothe user. In this case, advertisers are discouraged from sendingadvertisements to users who have little to no interest in theadvertisement.

In one embodiment, the social networking system 130 determines the priceto be charged to the merchant affiliated with the notification forproviding the notification to the user. In another embodiment, thesocial networking system waits until after an indication has beenreceived that the notification has been received, interacted with, orhas altered the user's behavior to determine a price to be charged tothe merchant affiliated with the notification. In these embodiments, theprice may also be based on the user's behavior, for example receiving anindication that caused a user merely to enter a store after receiving anotification may result in a notification costing a first price, whereasreceiving an indication that a user made a purchase after receiving anotification may result in a notification costing a second, higherprice.

The social networking system 130 receives notification feedbackregarding the behavior of the user in response to the notification. Thenotification feedback may comprise one or more of an updated userlocation, an indication that the user made a purchase from theaffiliated merchant including whether the user made use of a providedcoupon, a purchase amount, or an indication that the user paid for apurchase with a credit card or other payment system affiliated with thesocial networking system 130.

The notification feedback may be used for a number of different purposesdepending upon the embodiment. If the merchant is paying fornotifications based on the results generated by the notification, thesocial networking system uses the notification feedback to price thenotification. The notification feedback may also be used to adjust theprice of future notifications. For example if the ad was ineffective,the price of the ad may be reduced in the future. In one embodiment, thenotification feedback may be used to adjust the relevance score, andtherefore the price, for the third-party content object associated withthe notification. For example, an indication that a purchase was madebased on a notification may be used to increase the interest value ofthe third party content object associated with the notification, whichmay thereby increase or decrease the price for that advertisementdepending upon pricing structure implemented by the social networkingsystem 130. Similarly, if the notification was determined to be relevantbased on a high connection value, the connection value may be increasedas a result of the purchase.

Due to the dynamic nature of their generation, it is desirable toprovide merchants with a method controlling the distribution and amountthey pay for their notifications. FIG. 10 is a sample screenshotillustrating one embodiment of an advertisement dashboard allowing amerchant to control the distribution of advertisements provided to usersof a social networking system. The advertisement dashboard allowsmerchants to control how their advertisements are distributed by biddingon the price they are willing to pay to have their advertisementsdistributed with respect to specific third-party content objects.

The advertisement dashboard comprises a search tool 1040 allowingmerchants to search for individual third-party content objects, and agraph 1005 illustrating the bidding structure for individual third-partycontent objects. In one embodiment, each third-party content object maybe associated with more than one search query keyword, so that eachthird-party content object may be associated with a range of relatedgoods or services. The graph of each third-party content objectillustrates the advertisement bidding price 1010 on the Y-axis, for ahypothetical relevance score 1015 on the X-axis.

Merchants may exert a differing amount over control over the pricing anddistribution of their advertisements. The advertisement dashboardcomprises an automatic control radio button 1035 granting the socialnetworking system 130 permission to handle the pricing and distributionof advertisements. If this radio button is checked, the socialnetworking system 130 uses relevance scores, or any of the constituentvalues that make up the relevancy score, to automatically determine thebid price for a merchant for a given third-party content object. The bidprice may also vary depending upon the number of merchants seeking toadvertise for each particular third-party content object, the number ofnotifications that are sought to be pushed to the user within a giventime frame or within a given geographic area.

The advertisement dashboard also comprises a manual control radio button1030 allowing a merchant to manually control the distribution of theiradvertisements. If social networking system 130 receives an indicationthat the merchant wishes to manually control the bid price of theiradvertisements, the graph 1005 is displayed such that the merchant maychoose a bid price 1025 at a particular cost 1020 and maximum relevancescore bid 1045.

As described above, the social networking system 130 determines theprice of an advertisement provided to the user on the basis of therelevance of the advertisement to the user. By aggregating all relatedadvertisements provided to users across a range of prices and relevancescores, the system 130 is able to plot the price of an advertisement asa function of relevance score. The price of an advertisement as afunction of relevance score is plotted on the advertisement dashboard asa curve 1005. This curve represents the hypothetical relevance score andprice of an advertisement for a hypothetical user. Thus, a merchantwishing to bid on advertisements may get a sense of what advertisementsof varying relevance scores are going to cost.

The advertisement bid price 1025 represents the price paid by themerchant for providing an advertisement related to the searched onthird-party content object up to a maximum relevance score bid 1045. Themaximum relevance score bid 1045 is where the advertisement bid pricecrosses the curve 10005. Using the example of FIG. 10, if a notificationis to be sent to the user with a relevance score of 0.7 or less, and themerchant has the highest submitted advertisement bid price 1020 relativeto other merchants bidding on the same third-party content object, thenthe merchant's advertisement will be pushed to the user at a price basedon the relevance of the advertisement. Due to the fact that the socialnetworking system limits the maximum number notifications that may bepushed to a user, and because a notification is more likely to getpushed if it has a higher relevance score, more relevant advertisementscost more. Further, the more a merchant is willing to bid for anadvertisements related to a given third-party content object, the morelikely their notifications will get pushed. In other embodiments, ifmultiple merchants have bid on an advertisement to be pushed to a userwith a given relevance score, other factors may be taken into account inorder to determine which merchants advertisement to push. For example,the chosen merchant may be based on frequency past of notifications tothe user, or more strongly weighting values such as the location value.

In the example of FIG. 10, the merchant has chosen a bid price that is10 cents cost per thousand ads (CPM), which corresponds to a relevancyscore of 0.7. As a result, the merchant has bid a sufficiently highprice to have paid for notifications to be sent to users where therelevancy of the notifications to users will have a relevancy score ofless than or equal to 0.7. In order for the merchant to have theirnotifications provided to users for whom the notification would be morerelevant (e.g., a relevancy score of greater than 0.7), the merchantwill have to bid a higher price.

In one embodiment, the advertisement dashboard can break down therelevancy category into its constituent value scores, so that merchantsmay bid on the price of advertisements based upon the individual valuesthat the relevance score is based on. In order to specify bid pricesbased on these different values, the merchant many define one or moremarket segmentations. Market segmentations are divisions between groupsof user of users based on one or more segmentation criteria.Segmentation criteria may include, for example, relevancy by age,gender, location, time-of-day, preferences, expected budget, loyalty,affiliations, or any combination thereof. In this embodiment, merchantsmay bid for advertisements according to provided market segmentationcriteria. As a result, merchants may carefully define whichadvertisements they are bidding for.

Summary

The foregoing description of the embodiments of the invention has beenpresented for the purpose of illustration; it is not intended to beexhaustive or to limit the invention to the precise forms disclosed.Persons skilled in the relevant art can appreciate that manymodifications and variations are possible in light of the abovedisclosure.

Some portions of this description describe the embodiments of theinvention in terms of algorithms and symbolic representations ofoperations on information. These algorithmic descriptions andrepresentations are commonly used by those skilled in the dataprocessing arts to convey the substance of their work effectively toothers skilled in the art. These operations, while describedfunctionally, computationally, or logically, are understood to beimplemented by computer programs or equivalent electrical circuits,microcode, or the like. Furthermore, it has also proven convenient attimes, to refer to these arrangements of operations as modules, withoutloss of generality. The described operations and their associatedmodules may be embodied in software, firmware, hardware, or anycombinations thereof.

Any of the steps, operations, or processes described herein may beperformed or implemented with one or more hardware or software modules,alone or in combination with other devices. In one embodiment, asoftware module is implemented with a computer program productcomprising a non-transitory computer-readable medium containing computerprogram code, which can be executed by a computer processor forperforming any or all of the steps, operations, or processes described.

Embodiments of the invention may also relate to an apparatus forperforming the operations herein. This apparatus may be speciallyconstructed for the required purposes, and/or it may comprise ageneral-purpose computing device selectively activated or reconfiguredby a computer program stored in the computer. Such a computer programmay be stored in a non-transitory, tangible computer readable storagemedium, or any type of media suitable for storing electronicinstructions, which may be coupled to a computer system bus.Furthermore, any computing systems referred to in the specification mayinclude a single processor or may be architectures employing multipleprocessor designs for increased computing capability.

Embodiments of the invention may also relate to a product that isproduced by a computing process described herein. Such a product maycomprise information resulting from a computing process, where theinformation is stored on a non-transitory, tangible computer readablestorage medium and may include any embodiment of a computer programproduct or other data combination described herein.

Finally, the language used in the specification has been principallyselected for readability and instructional purposes, and it may not havebeen selected to delineate or circumscribe the inventive subject matter.It is therefore intended that the scope of the invention be limited notby this detailed description, but rather by any claims that issue on anapplication based herein. Accordingly, the disclosure of the embodimentsof the invention is intended to be illustrative, but not limiting, ofthe scope of the invention, which is set forth in the following claims.

1. A computer-implemented method for timing notifications of third-partycontent objects to a user of a social networking system, the methodcomprising: identifying third-party content objects associated with auser of the social networking system; establishing, for each of aplurality of time periods of a day, a maximum rate at which to providenotifications of third-party content objects to the user; providing afirst set of notifications of third-party content objects to a userdevice of the user at the maximum rate for each of the plurality of timeperiods; identifying user interactions with the first set ofnotifications; identifying patterns in the user interactions describingcharacteristics of the user's interactions with the first set ofnotifications; adjusting the maximum rate for each of the plurality oftime periods based at least in part on the identified patterns; andproviding a second set of notifications of third-party content objectsto the user device at the adjusted maximum rate for each of theplurality of time periods.
 2. The computer-implemented method of claim1, wherein the third-party content objects comprise informationalcontent objects describing at least one of movie show times, moviereviews, restaurant menus, restaurant reviews, product information, andproduct reviews of interest to the user.
 3. The computer-implementedmethod of claim 1, wherein the third-party content objects compriseincentive content objects describing at least one of coupons, discounts,promotions, or gift certificates of interest to the user.
 4. Thecomputer-implemented method of claim 1, wherein the plurality of timeperiods for the day comprise a time period associated with working hoursand a time period associated with home hours.
 5. Thecomputer-implemented method of claim 1, wherein each of the plurality oftime periods for the day are specified as an hour range.
 6. Thecomputer-implemented method of claim 1, wherein establishing, for eachof the plurality of time periods, the maximum rate at which to providenotifications of third-party content objects comprises: identifying adefault maximum rate of the social networking system at which to providethe notifications of the third-party content objects to the user deviceof the user.
 7. The computer-implemented method of claim 1, whereinestablishing, for each of the plurality of time periods, the maximumrate at which to provide notifications of third-party content objectscomprises: accessing user preference settings for the user; andidentifying, from the user preference settings, a user specified maximumrate at which to provide the notifications of the third-party contentobjects.
 8. The computer-implemented method of claim 1, furthercomprising: receiving user preference settings describing a userspecified maximum rate at which to provide the notifications of thethird-party content objects; and providing the second set ofnotifications at the user specified maximum rate rather than theadjusted maximum rate.
 9. The computer-implemented method of claim 1,wherein identifying the patterns in the user interactions describing thecharacteristics of the user's interactions with the first set ofnotifications comprises: identifying at least one of the plurality oftime periods for the day in which the user most frequently interactedwith the first set of notifications; and increasing the maximum rate inwhich to provide notifications of third-party content objects during theidentified time period in which the user most frequently interacted withthe first set of notifications.
 10. The computer-implemented method ofclaim 1, wherein identifying the patterns in the user interactionsdescribing characteristics of the user's interactions with the first setof notifications comprises: identifying a geographic location of theuser in which the user most frequently interacted with the first set ofnotifications; and increasing the maximum rate in which to providenotifications of third-party content objects when the user is located atthe geographic location.
 11. The computer-implemented method of claim 1,wherein identifying the patterns in the user interactions describingcharacteristics of the user's interactions with the first set ofnotifications comprises: identifying a type of content object from thefirst set of notifications most frequently interacted with by the user;and providing notifications of third-party content objects of theidentified type to the client device at the maximum rate.
 12. Acomputer-implemented method for adjusting when to provide notificationsof third-party content objects to a user of a social networking system,the method comprising: identifying third-party content objectsassociated with a user of the social networking system; determining arate at which to provide the third-party content objects to the userduring each of a plurality of time periods of a day; providingnotifications of the third-party content objects to a user device of theuser at the rate for the plurality of time periods; identifying userinteractions with the notifications; and adjusting the rate for theplurality of time periods based at least in part on the receivedinteractions.
 13. The computer-implemented method of claim 12, whereindetermining the rate at which to provide the third-party content objectsto the user comprises: identifying a default maximum rate of the socialnetworking system at which to provide the notifications of thethird-party content objects to the user device of the user.
 14. Thecomputer-implemented method of claim 12, wherein determining the rate atwhich to provide the third-party content objects to the user comprises:accessing user preference settings for the user; and identifying, fromthe user preference settings, a user specified maximum rate at which toprovide the notifications of the third-party content objects.
 15. Thecomputer-implemented method of claim 12, further comprising: receivinguser preference settings describing a user specified maximum rate atwhich to provide the notifications of the third-party content objects;and providing a second set of notifications at the user specifiedmaximum rate rather than the adjusted maximum rate.
 16. Thecomputer-implemented method of claim 12, further comprising: identifyingat least one of the plurality of time periods for the day in which theuser most frequently interacted with the first set of notifications; andincreasing the maximum rate in which to provide notifications ofthird-party content objects during the identified time period in whichthe user most frequently interacted with the notifications.
 17. Acomputer-implemented method for adjusting when to provide notificationsof third-party content objects to a user of a social networking system,the method comprising: identifying a first set of third-party contentobjects associated with a user of the social networking system;determining a delivery time range associated with the first set ofthird-party content objects describing when to provide the third-partycontent objects; determining whether to provide notifications of thefirst set of third-party content objects to a user device of the userbased on the delivery time range and when a last notification ofthird-party content objects was provided to the client device; providingthe notifications of the first set of third-party content objects to theuser device based on the determination; identifying user interactionswith the notifications; and adjusting the rate at which to provide asecond set of notifications of third-party content objects based atleast in part on the received interactions.
 18. The computer-implementedmethod of claim 17, further comprising: identifying a time period duringthe delivery time range in which the user most frequently interactedwith the first set of notifications; and increasing the maximum rate inwhich to provide notifications of third-party content objects during theidentified time period in which the user most frequently interacted withthe notifications.
 19. The computer-implemented method of claim 18,wherein the third-party content objects comprise informational contentobjects describing at least one of movie show times, movie reviews,restaurant menus, restaurant reviews, product information, and productreviews of interest to the user.
 20. The computer-implemented method ofclaim 18, wherein the third-party content objects comprise incentivecontent objects describing at least one of coupons, discounts,promotions, or gift certificates of interest to the user.